Content publishers, such as advertisers, are often limited in the amount of space that they can utilize to present content to a user at any given time. For example, an online advertiser may have specific dimensions (e.g., measured in centimeters, pixels, etc.) within which advertising material must be confined if it is to be presented to a user alongside a video being viewed, a game being played, in a search results listing, and the like. As such, content publishers often generate content that is made up of a number of different components selected to make full use of the available space while also conveying the intended information. For example, an online advertisement may contain a discount for a particular product or service being offered at some location or by some business, and may include a relevant image or video to better capture the user's attention.
A user who likes or enjoys certain content, such as an advertisement or a webpage, may wish to make his or her appreciation of the content known to one or more other users (e.g., in a social network of the user, or publicly). Accordingly, the user may make a recommendation of the ad or webpage that other users can see when they are presented with the same content. However, because such content often contains a variety of information, it can be difficult for advertisers to determine which component(s) of the content actually prompted the user to make the recommendation.